
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "182"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 116 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 108 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.034747	-0.587899	13.717184	8.156646	6.596750	111.823433	10.178866	8.390740	0.7781	0.7642	0.2609	8.391432	8.093945
2459593	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.778650	0.322004	17.352705	30.240740	9.976556	250.415529	4.937126	12.017449	0.7365	0.7231	0.2560	5.071728	4.965949
2459592	RF_maintenance	100.00%	0.00%	0.00%	0.00%	-	-	3.379395	3.797608	51.170204	16.789516	16.874086	50.429127	-0.898709	12.776710	0.7101	0.6975	0.4552	nan	nan
2459591	RF_maintenance	100.00%	0.00%	3.24%	0.00%	100.00%	0.00%	4.234440	2.078894	20.051365	15.865699	8.592268	103.003781	-1.687377	17.788498	0.6788	0.6705	0.3678	6.782691	6.512935
2459590	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	4.330569	2.711814	17.859764	6.266284	9.497627	144.567366	-0.299475	2.619009	0.6802	0.6391	0.3740	6.141888	5.343375
2459589	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.325369	3.013547	15.345619	16.181092	5.973447	8.590045	7.722807	7.648050	0.7113	0.7040	0.2858	5.002315	4.431594
2459588	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.977511	0.216525	20.881434	54.937594	7.343807	144.198652	7.031196	8.968424	0.7775	0.7369	0.2367	7.430931	7.190017
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	354.008611	354.404795	inf	inf	100.732907	101.196988	606.514966	604.972662	nan	nan	nan	0.000000	0.000000
2459586	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	312.231691	312.373842	inf	inf	17.709383	15.723552	665.816273	682.979909	nan	nan	nan	0.000000	0.000000
2459585	RF_maintenance	100.00%	0.00%	20.90%	0.00%	100.00%	0.00%	35.288631	28.708274	21.421387	6.715933	6.914424	10.551032	-0.452759	20.429107	0.6438	0.4962	0.3926	0.000000	0.000000
2459584	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	938.330869	606.085210	inf	inf	3285.507170	2643.256059	21268.231735	15750.803065	nan	nan	nan	0.000000	0.000000
2459583	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.207070	13.545981	8.522237	29.205107	6.930133	27.642147	-1.192691	5.651967	0.6812	0.5486	0.4101	3.854689	2.664709
2459582	RF_maintenance	100.00%	0.00%	7.57%	0.00%	100.00%	0.00%	3.059341	10.406674	7.908947	24.686904	8.425927	44.060213	-1.321280	11.557735	0.6809	0.5661	0.4105	3.638787	2.600040
2459581	RF_maintenance	100.00%	0.00%	9.73%	0.00%	100.00%	0.00%	4.459083	1.526790	7.975737	10.269627	6.577990	148.239116	-1.066489	19.828218	0.6885	0.6194	0.3907	3.307279	2.841015
2459580	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.527073	2.372289	9.016957	6.974080	7.736124	2.725903	-0.930563	20.278145	0.6819	0.6881	0.3787	4.004602	4.015815
2459579	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.513977	3.712482	10.418022	4.708023	8.388179	89.409388	-1.731654	36.756095	0.6769	0.6721	0.3797	34.176956	39.711313
2459578	RF_maintenance	100.00%	0.00%	0.00%	0.00%	-	-	4.907873	4.045559	28.739794	24.500912	14.599366	35.550944	9.163517	116.715226	0.7346	0.7491	0.4709	nan	nan
2459577	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459576	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.060839	3.595286	5.726823	6.200588	6.988835	9.585943	0.265287	0.222206	0.6999	0.7042	0.3788	5.459715	4.951655
2459575	RF_maintenance	100.00%	0.00%	12.97%	0.00%	100.00%	0.00%	2.228507	3.357391	6.132273	0.612226	6.128396	113.587620	4.734151	3.589835	0.7493	0.6068	0.3672	4.695863	4.050551
2459574	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459573	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.896440	2.503291	11.295111	2.727029	8.790562	78.564369	-1.567462	22.997356	0.6999	0.7083	0.3745	4.291701	4.008184
2459572	RF_maintenance	100.00%	0.00%	1.62%	0.00%	100.00%	0.00%	3.597919	2.829082	5.802445	1.771997	6.108363	111.770375	-2.222297	3.571024	0.7023	0.6568	0.3912	4.304353	3.660703
2459571	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	nan	nan
2459570	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.838243	-0.545650	-0.999243	-0.636461	-0.978254	-0.638362	-0.419156	-0.316138	0.6930	0.7002	0.3531	12.663959	13.566736
2459569	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.618777	2.818807	6.704012	7.130934	5.773215	12.177334	4.721285	4.783441	0.7659	0.7685	0.2373	4.172814	3.827338
2459566	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.506638	0.638144	7.955719	1.683471	6.949061	11.060094	-1.274583	2.845206	0.6920	0.7057	0.3942	3.172091	3.060165
2459565	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	-0.000390	-0.000390	0.000000	0.000000	-0.823769	-0.823769	-0.908427	-0.908427	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	100.00%	0.00%	20.82%	0.00%	100.00%	0.00%	-0.129152	2.445018	-0.445304	12.638706	-1.523535	36.144711	-0.578452	14.482453	0.7067	0.6227	0.4089	3.301506	2.924546
2459563	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.567959	1.413895	17.010551	2.325130	7.978224	54.677653	-0.430446	13.001901	0.7057	0.7077	0.3863	4.185354	3.981118
2459562	RF_maintenance	100.00%	0.00%	2.70%	0.00%	100.00%	0.00%	-0.609480	-1.223648	-0.707707	-2.229198	-2.138407	28.626322	-0.894399	4.532211	0.7073	0.7012	0.3844	3.112554	2.915782
2459561	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.435374	-0.564018	-0.165131	-2.040204	-1.725109	15.802635	-1.811462	3.963687	0.7047	0.7129	0.3820	2.811381	2.696814
2459560	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.274870	-0.931149	-0.569625	-1.177822	-1.515668	-1.824370	-1.114895	2.897678	0.7061	0.7148	0.3931	3.059344	2.893736
2459559	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.118277	-0.560548	-0.042957	-0.595720	-1.103574	-0.261879	-0.858179	0.931063	0.6984	0.7082	0.3853	2.651810	2.630663
2459558	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	4.011761	2.593471	9.229105	6.064707	8.135216	52.860624	-1.360784	5.407990	0.7083	0.7078	0.3850	3.477722	3.294972
2459557	RF_maintenance	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7441	0.6940	0.4187	nan	nan
2459556	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	4.092829	4.165835	9.624161	3.580827	7.436985	133.671614	-2.404142	2.397297	0.7008	0.6622	0.3942	3.724283	3.068120
2459554	RF_maintenance	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7099	0.7123	0.3911	nan	nan
2459553	RF_maintenance	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7041	0.7051	0.3920	nan	nan
2459552	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	4.520409	5.532005	12.545298	13.984639	12.196972	15.588013	-0.397641	-0.136151	0.7088	0.7074	0.3918	8.490881	8.775144
2459551	RF_maintenance	100.00%	0.00%	69.15%	0.00%	100.00%	0.00%	-0.174934	4.576799	-0.420973	16.939395	-2.365428	54.228742	-1.204079	9.700316	0.7075	0.2767	0.4611	3.024318	1.275441
2459550	RF_maintenance	-	28.83%	99.18%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.5088	0.0595	0.1786	nan	nan
2459549	RF_maintenance	100.00%	0.00%	100.00%	0.00%	100.00%	0.00%	3.435740	18.058576	9.145105	38.372929	7.752158	22.489160	-1.001350	2.468769	0.6989	0.1096	0.4841	3.517544	1.302947
2459542	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459541	RF_maintenance	100.00%	1.34%	1.34%	0.00%	100.00%	0.00%	3.603101	3.420192	11.426433	11.448069	7.024817	8.549229	3.477860	4.284004	0.7414	0.7332	0.3354	4.669015	4.088851
2459540	RF_maintenance	100.00%	0.00%	14.77%	0.00%	100.00%	0.00%	1.280370	1.358566	1.202805	3.986532	-1.300951	189.972039	-1.146527	3.488087	0.7507	0.5851	0.4010	2.801526	1.571498
2459536	RF_maintenance	100.00%	0.00%	3.71%	0.00%	100.00%	0.00%	5.066010	2.733578	15.160537	14.772642	13.539064	230.775560	-1.326666	30.109479	0.7283	0.6328	0.4439	5.187843	4.192413
2459535	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.656057	1.459385	0.791247	5.004045	-2.097747	1.209915	-0.874560	12.293346	0.7869	0.7648	0.3634	2.708630	2.394670
2459534	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.053581	1.514999	-0.132070	4.676833	-2.283004	0.873511	-0.848223	10.426004	0.7726	0.7465	0.3696	3.738040	3.108339
2459533	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459532	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	4.756691	3.787366	12.583330	16.219043	9.071874	9.821965	-1.456490	22.211022	0.7250	0.7195	0.3926	3.875597	3.306355
2459530	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.023193	1.384199	-0.189956	3.242395	-1.933392	3.240710	-0.601076	13.631446	0.7367	0.7317	0.3882	3.440544	3.061622
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	5.074411	3.882058	10.193010	11.601989	18.931878	5.410412	-0.511855	13.872686	0.8963	0.9301	0.3245	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	4.802164	2.688186	13.579784	12.717326	5.965319	0.546220	-3.916567	23.358405	nan	nan	nan	5.094363	4.416211
2459522	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	4.037537	2.613042	12.592558	10.531220	3.624200	5.455940	-0.319678	26.171479	0.6750	0.6620	0.3493	4.413509	5.373515
2459513	RF_maintenance	100.00%	0.00%	0.00%	0.00%	-	-	5.018137	5.262097	28.422123	29.426841	14.399523	33.538084	3.811117	84.321967	0.8385	0.8460	0.2653	nan	nan
2459508	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	4.733286	23.940573	8.168612	49.680426	7.581755	20.436122	7.342984	10.272991	0.9011	0.7862	0.2954	0.000000	0.000000
2459505	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	4.386279	22.368391	10.398810	44.408210	1.687538	10.475229	-1.183611	6.182562	0.8807	0.6683	0.3751	24.309155	13.315982
2459503	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	7.528758	1.721056	10.681499	2.212452	17.474430	3.401370	-0.778107	9.308947	0.8650	0.8657	0.4617	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 182 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 182, Node 13:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 182: 2459642

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Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶